code: def get_model_from_layers(
      layers,
      input_shape,
      input_sparse=False,
      input_ragged=False,
      input_dtype=None,
  ):
      layers = [
          tf.keras.Input(
              shape=input_shape,
              dtype=input_dtype,
              sparse=input_sparse,
              ragged=input_ragged,
          )
      ] + layers
      return tf.keras.models.Sequential(layers)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
  from tensorflow_text.python.keras.layers.todense import ToDense
label_desc: Use image node_id 2 for calling a global function with example usage: get_model_from_layers(layers, input_shape, input_sparse, input_ragged, input_dtype) and returns: tf